import matplotlib.pyplot as plt
import pandas as pd
from IPython.display import Image

# This is the color scheme I use throughout the CV
CV_COLORS = ['#cc99ff', '#ff99cc', '#ffcc99', '#ffff99', '#ccffcc', '#ccffff', '#99ccff']

Image(filename='images/pinar.JPG', width=150, height=150) 

jobs = pd.read_csv('./data/jobs.csv')
explode = (0, 0, 0, 0, 0.1)
pie = jobs.plot.pie(y='Duration / Month', explode=explode, labels=jobs['Employer'], colors=CV_COLORS, autopct='%1.0f%%')
pie.get_legend().remove()
plt.title('Work experience', weight='bold', size=14)
plt.ylabel("")
plt.tight_layout()
plt.show()
plt.clf()
plt.close()

skills = pd.read_csv('./data/skills.csv')


groups = ["Programming Language", "Framework", "Tool"]
fig, ax = plt.subplots()
fig.set_size_inches(8, 6) 

for group in groups:
    skill = skills[skills.Type == group]
    ax.plot(skill['Number of month practiced'], 
            skill['Competency Level'], 
            marker='o', 
            linestyle='', 
            ms=20, 
            label=group)
    for i, txt in enumerate(skill.Skill):
        ax.annotate(txt, (skill['Number of month practiced'].iat[i],
                          skill['Competency Level'].iat[i]), 
                    xytext=(5,-5), 
                    textcoords='offset points',)
ax.legend()
ax.set_xlim(0, 25)
plt.xlabel('Number of month practiced')
plt.ylabel('Competency Level')
plt.title("Skill Competency Matrix")
plt.show()

import plotly.express as px
import pandas as pd
%matplotlib inline
 
source = pd.DataFrame([
    {"Education": "BSc- Physics", "start": '2000-09-01', "end": '2005-06-01', "where": 'Hacettepe University'},
    {"Education": "MSc- Physics Teaching","start": '2005-09-01', "end": '2006-06-01', "where": 'Hacettepe University'},
    {"Education": "MSc- Physics Engineering","start": '2006-09-01', "end": '2008-06-01', "where": 'Hacettepe University'},
    {"Education": "PhD- Physics / Chemistry","start": '2008-10-03', "end": '2011-10-15', "where": 'University Bordeaux I'},
    {"Education": "MSc- Data Science","start": '2021-09-15', "end": '2023-08-31', "where": 'The University of Edinburgh'}])
 
source['start'] = pd.to_datetime(source['start'])
source['end'] = pd.to_datetime(source['end'])

fig = px.timeline(source.sort_values('start'),
                  x_start="start",
                  x_end="end",
                  y="Education",
                  text="where",
                  color_discrete_sequence=["tan"],
                 width=1000, height=400)
fig.update_traces(textposition='auto')
fig.show()